NATURE INSPIRED ALGORITHM BASED OPTIMAL TYPE-2 FUZZY CONTROLLER WITH REAL-TIME VALIDATION ON SERVO SYSTEM

Performance of three well-known nature inspired algorithms like genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution algorithm (DE) towards selection for optimal input and output scaling factors of an interval type-2 fuzzy PID controller (IT2-FLC) is evaluated for servo position control system. Optimal values of the input and output scaling factors for IT2-FLC are obtained through minimization of the objective function designed involving controller performance indices – percentage overshoot, settling time and integral time absolute error. Simulation study along with real-time experimental validation reveal the (DE) based optimal IT2-FLC in terms of robustness and lesser noise sensitivity compared to other optimal IT2-FLCs.